Niklas Hanselmann

16 papers A* 2C 1Journal 11Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
What Matters for Scalable and Robust Learning in End-to-End Driving Planners?
CoRR
David Holtz, Niklas Hanselmann, Simon Doll, Marius Cordts, Bernt Schiele
2025 J jnl
AGO: Adaptive Grounding for Open World 3D Occupancy Prediction.
CoRR
Peizheng Li, Shuxiao Ding, You Zhou, Qingwen Zhang, Onat Inak, Larissa Triess, Niklas Hanselmann, Marius Cordts, Andreas Zell
2025 J jnl
Emperror: A Flexible Generative Perception Error Model for Probing Self-Driving Planners.
IEEE Robotics Autom. Lett.
Niklas Hanselmann, Simon Doll, Marius Cordts, Hendrik P. A. Lensch, Andreas Geiger
2024 J jnl
DualAD: Disentangling the Dynamic and Static World for End-to-End Driving.
CoRR
Simon Doll, Niklas Hanselmann, Lukas Schneider, Richard Schulz, Marius Cordts, Markus Enzweiler, Hendrik P. A. Lensch
2024 A* conf
Dualad: Disentangling the Dynamic and Static World for End-to-End Driving.
CVPR
Simon Doll, Niklas Hanselmann, Lukas Schneider, Richard Schulz, Marius Cordts, Markus Enzweiler, Hendrik P. A. Lensch
2024 J jnl
EMPERROR: A Flexible Generative Perception Error Model for Probing Self-Driving Planners.
CoRR
Niklas Hanselmann, Simon Doll, Marius Cordts, Hendrik P. A. Lensch, Andreas Geiger
2024 J jnl
S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking With Adaptive Spatio-Temporal Appearance Representations.
IEEE Robotics Autom. Lett.
Simon Doll, Niklas Hanselmann, Lukas Schneider, Richard Schulz, Markus Enzweiler, Hendrik P. A. Lensch
2023 A* conf
PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird's-Eye View.
IJCAI
Peizheng Li, Shuxiao Ding, Xieyuanli Chen, Niklas Hanselmann, Marius Cordts, Juergen Gall
2023 J jnl
PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird's-Eye View.
CoRR
Peizheng Li, Shuxiao Ding, Xieyuanli Chen, Niklas Hanselmann, Marius Cordts, Juergen Gall
2023 J jnl
S.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations.
CoRR
Simon Doll, Niklas Hanselmann, Lukas Schneider, Richard Schulz, Markus Enzweiler, Hendrik P. A. Lensch
2022 — conf
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients.
ECCV (38)
Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, Andreas Geiger
2022 J jnl
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients.
CoRR
Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, Andreas Geiger
2022 — conf
Unsupervised Domain Adaptive Object Detection with Class Label Shift Weighted Local Features.
ECCV Workshops (2)
Andong Tan, Niklas Hanselmann, Shuxiao Ding, Federico Tombari, Marius Cordts
2021 C conf
Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation.
IV
Niklas Hanselmann, Nick Schneider, Benedikt Ortelt, Andreas Geiger
2021 J jnl
Learning Cascaded Detection Tasks with Weakly-Supervised Domain Adaptation.
CoRR
Niklas Hanselmann, Nick Schneider, Benedikt Ortelt, Andreas Geiger
2020 J jnl
Visibility Guided NMS: Efficient Boosting of Amodal Object Detection in Crowded Traffic Scenes.
CoRR
Nils Gählert, Niklas Hanselmann, Uwe Franke, Joachim Denzler